Seminar: Moral Flexibility in Human and Machine Minds

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Sydney Levine, Allen Institute for Artificial Intelligence

Moral Flexibility in Human and Machine Minds

One of the most remarkable things about the human moral mind is its flexibility: we can make moral judgments about cases we have never seen before.Yet, on its face, morality often seems like a highly rigid system of clearly defined rules. Indeed, the past few decades of research in moral psychology have revealed that human moral judgment often depends on rules. But sometimes, it is morally appropriate to break the rules. And sometimes, new rules need to be created. The field of moral psychology is just now beginning to explore and understand this kind of flexibility. Meanwhile, the flexibility of the human moral mind poses a challenge for AI engineers. Current tools for building AI systems fall short of capturing moral flexibility and thus struggle to predict and produce human-like moral judgments in novel cases that the system hasn’t been trained on. I will present a series of experiments and models that demonstrate and capture the human capacity for rule making and breaking. I will then discuss a series of ongoing projects that draw inspiration from these models to develop AI systems that make human-like moral judgments.

Sydney Levine is a Research Scientist at the Allen Institute for Artificial Intelligence. Her research uses tools from cognitive science and philosophy to understand the human moral mind and to develop AI systems that can predict and produce human moral judgment. She received a PhD in psychology from Rutgers University, where she studied the development of morality in preschool-aged children. She then trained as a postdoc at Harvard and MIT, where she worked on developing computational models of human moral judgment. Her current work sits at the intersection of cognitive science and AI development, exploring ways that insights in one field can inspire progress in the other.

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